jev-align: Build calibrated AI Functions from human feedback using Jev and GEPA

by sutro-sh · AI Tool · ★ 315

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install jev-align

uv tool install jev-align

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 73/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

active-learningclassificationcligepahuman-in-the-loopjevprompt-optimizationtypesafe-ai

Quick Facts

Stars315
Forks25
LanguagePython
CategoryAI Tool
LicenseApache-2.0
Quality Score73/100
Open Issues1
Last Updated2026-10-28
Created2026-09-19
Platformscli, python
Est. Tokens~14k

About jev-align

jev-align is an experimental CLI from Sutro for building AI Functions with TypeSafe's Jev. It finds uncertain examples, asks you to label them, and uses GEPA to improve the function. Use it in your application and keep learning from production examples. Demo https://github.com/user-attachments/assets/81650587-e3f1-4655-8213-ed5f6e120e9a Quick start Requires Python 3.11 or newer.

Compatible Skills

These tools work well together with jev-align for enhanced workflows:

  • OpenDecision — semantic(0.64)+complementary+same_lang+similar_pop+shared_platform (73%)
  • open-alternative-jev — semantic(0.54)+complementary+same_lang+similar_pop+shared_platform (69%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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